Large-scale industrial Internet of Things (IIoT) deployments tend to stall out and fail before they even get started. From data collection problems to bad technology, there are numerous issues that prevent organizations from implementing digital projects successfully.
We’ve learned that many of these challenges exist as a result of how leaders approach IIoT deployments. They must choose between one of two IIoT design strategies -- “greenfield IoT” or “brownfield IoT.” Whether it's for a remote facilities management system, equipment monitoring, or production monitoring, the choice has important ramifications that leaders must consider.
Contextualizing this to the industrial IoT, greenfield IoT projects involve deploying technology simultaneously with new Things, usually by the original equipment manufacturer or a distributor, whereas brownfield IoT projects deploy on Things already in operation, perhaps by a full-stack vendor or systems integrator.
Side note: At WellAware, we take the concept of the Internet of “Things” at its word, so to speak. Instead of trying to define every “thing” that IIoT systems might connect to (e.g., equipment, assets, infrastructure), we choose to call them Things (with a capital T). To learn more about our approach to remote asset management, watch our webinar, "Remote Asset Management in 2020."
The difference between greenfield development and brownfield development seems minor, right?
Wrong.
Greenfield IoT and brownfield IoT approaches each present significant and unique challenges to success in digital transformation. Is one better than the other? Can we dispense with either approach?
Let’s dig in to find out.
On paper, greenfield IoT projects seem like a dream come true.
Business leaders get to design custom technology for their unique needs. New equipment is shipped directly from the factory floor and installed alongside the Things it will connect to the industrial internet. Nothing has to conform to existing infrastructure or processes.
On top of that, network designers understand the full scope of the project ahead of time. They don’t have to worry about issues surfacing that were previously hidden by legacy monitoring systems.
While this is all true, there is a catch.
When organizations commission custom-built Things from many vendors, each with distinct IIoT systems, technicians are inundated with operational complexity. To remotely monitor a tank farm or facility, for example, they will have to learn how to engage with tens or hundreds of IIoT systems that might not play nicely with each other.
It’s also difficult for plant managers and field workers to synchronize processes across these multiple systems, particularly those with unique standards and protocols.
Zooming out further, data aggregation is near impossible with greenfield projects, as every system is likely to store data in different ways. As a result, building a predictive maintenance program for all machinery wouldn’t be feasible with so many data streams to consolidate.
At the end of the day, industrial companies who buy IIoT solutions directly from OEMs or distributors typically either hire a systems integrator ($$$$) to bring everything into a single pane of glass, or they just stop short of getting everything integrated.
We see this all the time at WellAware. For example, a company may have their HVAC system from a certain vendor connected to a monitoring system, but their other lighting, mechanical, electrical, and plumbing systems from other OEMs remain disconnected and unoptimized.
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Many IIoT deployments thus far have followed the brownfield development approach.
Companies have used wireless technology over the past several years to digitize existing facilities, roads, farms, fields, factories, and more. In some cases, brownfield IoT projects can be less expensive and quicker to execute than greenfield IoT projects, as network designers don’t have to start from scratch.
However, the brownfield development strategy is not without its drawbacks
Controlling and automating Things is hard when devices use different languages and protocols. When installing IIoT devices, users or vendors have to navigate a complex set up and integration process. Devices still have to be evaluated, purchased, installed, configured, provisioned, and managed, even if network infrastructure is already in place.
Additionally, wireless technology is often installed in hazardous areas, making it difficult for field technicians to perform repairs or regular maintenance checks. In many cases, reaching devices requires cabling, trenching, or other labor-intensive methods.
It’s also common for brownfield IoT to require separate legacy devices, such as PLCs and RTUs, to handle inter-Thing communication. At best, these field computers are inefficient or expensive. At worst, they don’t work at all. Plus, they are just another type of Thing that field technicians have to manage.
On the data aggregation front, organizations still have to set up data lakes to ingest information from disparate devices. Analysts have to create user interfaces and ensure the right data hierarchies are in place to synthesize information gathered from the field.
When you boil it down, brownfield IoT ends up looking a lot like greenfield IoT, but for different reasons. Instead of grappling with integrating multiple types of technology systems into a single pane of glass, companies instead most figure out how to bring disparate makes and models of industrial equipment into a common IIoT architecture.
Like those who choose a greenfield development approach, proponents of brownfield development projects are probably looking at hiring a systems integrator, or stalling out on their dream of connecting their entire infrastructure.
To be successful with large-scale IIoT deployments, organizations have to solve the unification problem in the physical world, where disparate equipment speak numerous languages, and at the interface, where humans want and need to use multiple visualization, analytics, and intelligence tools to make decisions from equipment data.
This requires a full-stack vendor with open technology with the flexibility to support diversity at the edge and in the cloud. At WellAware, we call this the Integrated Data Value Journey. Vendors need to be able to solve the data challenges at every step of the journey data takes to create value for its users, from the physical world, through the communications layer, to cloud storage, and at the point of user interface. And of course, that needs to be done without hiring an expensive systems integrator.
We’ve built a platform AND a business model that does just that.
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